Sentence examples for better predictive performance from inspiring English sources

The phrase "better predictive performance" is correct and usable in written English.
It can be used in any context that requires an evaluation of the quality of predictive performance. For example, "The model showed better predictive performance when compared to its competitors."

Exact(59)

For instance, the AUC value of RF classifier for brain-specific gene prediction (AUC = 0.9488, Table 1) is higher than that for brain-selective gene prediction (AUC = 0.9178, Table 6), whereas the RF classifier gave better predictive performance for liver-specific gene prediction (AUC = 0.9777, Table 1) than liver-selective gene prediction (AUC = 0.9547, Table 6).

In statistical learning, we can often achieve better predictive performance by combining the predictions from multiple models.

The results indicate that the RF classifiers achieved better predictive performance for tissue-specific gene prediction.

All genic regions considered delivered a better predictive performance for BM and an inferior prediction for BW and HHP.

The experimental results, validated on the real-world data provided by DiDi Chuxing, show that the FCL-Net achieves the better predictive performance than traditional approaches including both classical time-series prediction models and state-of-art machine learning algorithms (e.g., artificial neural network, XGBoost, LSTM and CNN).

This approach enables better predictive performance from a simpler model.

Accuracy evaluation results showed that the BRT model had better predictive performance than the MLSR.

When it comes to limited data availability, a simple model may have a better predictive performance than a complex model.

However, the polynomial calibration equation had better predictive performance than the linear equation for the CTR-E200 meter.

In addition, current research has ignored the use of ensemble learning techniques, such Bagging or Boosting, to obtain better predictive performance than using the traditional learning algorithms.

The results show that HGA-FNN has a better predictive performance than GA-FNN and that it has good potential in terms of stability assessments of coastal structures.

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